Uncertainty Data in Interval-Valued Fuzzy Set Theory
Properties, Algorithms and Applications
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Beschreibung
This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.
This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.
Focuses on interval-valued fuzzy aggregations, and its importance for solving multi criteria decision making problems Describes fuzzy set based methods for dealing with incomplete knowledge Highlights the case of imprecise data represented as intervals
Autor*in
Barbara Pękala
Themen in »Uncertainty Data in Interval-Valued Fuzzy Set Theory«
Interval-Valued Fuzzy Aggregations Decision Making Using Preference Interval-Valued Fuzzy Relations Preservation of N-Reciprocity Applications of Aggregation Functions Compatibility Measures of Intervals Interval-Valued Ordered Weighted Averaging Operators Properties of Interval-Valued Fuzzy Relations Generalized Composition of Interval-Valued Fuzzy Relations Approximate Reasoning Using General Compositions